Managers and machines, unite!
Three things managers must do to
make the most of cognitive computing
by Ryan Shanks, Sunit Sinha and Robert J. Thomas
Intelligent machines are poised to dramatically shift management
roles as we know them. But many organizations aren’t prepared to
take full advantage of the change that lies ahead.
The rise of intelligent machines
Organizations are just starting to use intelligent machines—
information systems that sense, comprehend, act and learn—
to automate some of the more routine, rules-based tasks that
take up so much of managers’ time.
Coordinating processes, monitoring performance,
and scheduling resources and activities are prime
candidates for automation. With such applications,
companies will save money. But intelligent machines
will also free managers to focus on more strategic
issues and activities. That’s the game-changing
opportunity.
Intelligent machines inform better, faster decisions.
They enable managers to shift their focus to activities
that call for decidedly human traits such as complex
thinking and higher-order reasoning. Providing
guidance and recommendations, machines complement
managers’ expertise, experience and ethics, as well as
their ability to experiment and innovate. In all these
ways, intelligent machines open the door to “judgment
work,” which values intuition as much as, if not more
than, know-how. Our discussions with industry leaders
on the topic of intelligent machines revealed they are
particularly excited by the possibility for machines
to augment managers’ decision-making capabilities.1
For them, the real potential lies in helping managers
unleash an organization’s creative potential, capture
new growth opportunities, and lead a more empowered
workforce of the future.
Managers and machines, unite! |
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Three issues not covered
in the owner’s manual
CEOs and their leadership teams are understandably
excited by the prospects of a more dynamic managerial
workforce. But what do managers think? How do they
feel about the incursion of intelligent machines in their
work? Are they really prepared for the shift that is
under way?
The overwhelming majority of managers believe
machines will make them more effective and their work
more interesting. That’s one of the findings of a firstof-its-kind study of the impact of cognitive computing
in management by the Accenture Institute for High
Performance and Accenture Strategy (see Methodology
for more detail). However, the survey also revealed three
issues that might affect an organization’s ability to
make the most of a manager-machine union.
Managers underrate human skills
Managers believe their roles will need the following
skills in 5 years (top 3 skills selected)
Digital/Technology
42%
Creative thinking
and experimentation
33%
Data analysis
and interpretation
31%
Strategy
development
30%
Planning and
administration
23%
Social networking
21%
People development
and coaching
21%
Collaboration
20%
Quality management
and standards
20%
Sharpen skills
within my current
domain of expertise
20%
Performance
management
and reporting
17%
INTERPERSONAL SKILLS
Managers aren’t convinced they’re ready to thrive in a
workplace with more intelligent machines. Over half
(57 percent) responded that their current skills are
lacking. More troubling is the fact that managers have
an incomplete understanding of what they will need
to thrive in a partnership with intelligent machines.
A number of them recognize the need for digital skills,
creative thinking and strategy development. And that’s
important, because those are, in fact, skills they’ll
need to manage business complexity and growth.
What they overlook, however, is the importance of
the interpersonal skills they will need to manage their
people. They ranked social networking, people development and collaboration 6th, 7th and 8th in importance.
Only about a fifth of those we surveyed thought these
skills would be important to their roles in the future.
That’s a potential problem because managers will need
to inspire their teams and enable them to succeed. They
will need to learn how to interpret the analyses and
recommendations those machines provide to ask the
right questions and improve decision making. And they
will need to develop, coach and collaborate with others
to drive experimentation and innovation across the
organization.
Source: Accenture Institute for High Performance and Accenture Strategy,
“The Impact of Cognitive Computing in Management”, 2015.
Managers and machines, unite! |
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Resistance is stronger than leaders think
The path to value is unclear
Our findings suggest a paradox among respondents.
On the one hand, managers at all levels (84 percent)
believe machines will make them more effective and
their work more interesting. Yet only 14 percent of
first-line managers and 24 percent of middle managers
would readily trust the advice of intelligent systems in
making business decisions in the future. By contrast,
nearly half of senior executives (46 percent) would
readily trust the advice of intelligent systems.
Managers believe the greatest value of intelligent
machines lies in machines’ abilities to augment, not
automate, their work. Of 11 core management tasks,
they deem only one—monitoring and reporting
performance—to be a serious candidate for automation.
How can leaders close the trust gap? When asked
what would allow them to trust a system’s advice,
first-line and middle managers selected: providing a
solid understanding of how the system works and
generates advice (60 percent); choosing a system with a
proven track record (55 percent); and ensuring that the
system explains its logic (49 percent). By satisfying these
three conditions, leaders will be better positioned to
capture the synergies that are possible when machines
augment managers’ performance. Without trust, it’s
unlikely an organization will be able to do more than
automate a few routine managerial tasks.
84 percent of
managers at all levels believe
machines will make them
more effective and their
work more interesting.
The good news for leaders is that opportunities abound.
Augmentation can take many forms. Some managers
will use intelligent machines to work smarter and faster.
Sales managers, for example, might access machines’
near real-time analyses to adjust promotional campaigns
or pricing in direct response to demand fluctuations.
Intelligent machines could help department heads by
taking over routine and time-consuming tasks such as
management and financial reporting, allowing managers
to spend more time on strategic planning or the
development of new products and services. And for
others, intelligent machines will open doors to new
opportunities, responsibilities and ways of working. For
example, machines can now analyze the characteristics
of job applicants, predict which ones will leave, and
recommend strategies to get them to stay. HR managers
can use those insights to deliver on the promise of
customized HR—developing personalized coaching
programs and targeted interventions in a scalable way.
The potential for machines to elevate managerial
performance is exciting—but relatively unknown. Given
how recently intelligent machines have entered the
scene, there is no well-worn path to follow. But that
should not stop a cognitive computing rollout in its
tracks. Leaders should seize the opportunity to use their
human skills of experimentation to unearth innovative
ways to tap this new potential.
Managers and machines, unite! |
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Intelligent leadership in the
age of intelligent machines
CEOs and their leadership teams have a responsibility to ensure their
managers are prepared to take full advantage of the change that lies
ahead. Here are three things they can do to facilitate the shift:
Sharpen the human edge
To thrive, managers must have skills and behaviors that
will drive organizational performance. These include
analytical reasoning, digital know-how and business
acumen. But they also need interpersonal skills to build
teams, foster innovation and encourage new ways
of working.
To achieve the right skill levels and blend of capabilities,
leaders will likely need to revise their organizations’
existing training and coaching programs, as well as
individual performance criteria. The reality is that
some existing managers won’t be able to make the
shift required. For that reason, leaders will need to look
outside their organizations for managers who excel
in judgment work and are comfortable working with
machines. This means revisiting and realigning talent
sourcing, development and reward strategies.
Rally the troops
More than simply identifying the right smart technologies for their business, leaders must inspire their
managers to embrace new ways of working. They
need to tap their own interpersonal skills to create
excitement about how intelligent machines will shape
the future of work. As part of this, they will need to
convince their first-line and middle managers of the
value of intelligent machines. And they will need to
educate their managers (and themselves) about how
machines do what they do.
In addition to promoting intelligent machines as
trustworthy advisors, leaders must present themselves
as trustworthy advocates of change. Accenture
Strategy’s analysis of 250 major change initiatives
at more than 150 organizations2 has confirmed that
organizations with trusted leaders can implement and
accelerate change without first having to educate
employees about the specific details. This suggests that
managers will be more likely to commit emotionally to
the introduction of cognitive computing if they trust
the leaders at the helm. Building trust will require clear
and honest communications from day one. It also calls
for leaders to involve managers in the change. They
should encourage managers to share their insights,
suggestions, opinions—and even their fears—at every
step of the journey.
Chart a course of discovery
Businesses are just starting to scratch the surface of
what is possible when intelligent machines take over
certain tasks and complement others. There are a lot
of unknowns, which means leaders and their managers
must be willing to experiment to identify machine uses
that make the most sense for their organizations and
their teams. Launching targeted experiments and
learning from them in a structured way will help them
zero in on higher-value opportunities.
Ideally, CEOs should strive to create a union of
managers and machines that does more than automate
tasks or augment managers’ performance. The most
successful long-term unions will multiply the value that
managers or machines are able to deliver on their own.
Leaders can’t rely on intelligent machines to show them
the way forward. For that, they will need to rely on
experimentation, past experiences and their intuition.
They will, in effect, need to engage in judgment work of
the highest order.
Managers and machines, unite! |
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Toward a more perfect union
There is significant potential for intelligent machines to improve
enterprise performance at the management level. But to take full
advantage of what the cognitive computing revolution has to offer,
leaders must ensure that their organizations have the capacity
to change. Those that get it right will create a culture of
experimentation and trust among leaders at all levels. They will
be the ones to unlock the potential of the workforce of the future.
Managers and machines, unite! |
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Join the conversation
@AccentureStrat
Contact the Authors
Ryan Shanks
Dublin, Ireland
[email protected]
Sunit Sinha
Gurgaon, India
[email protected]
Robert J. Thomas
Boston, Massachusetts
[email protected]
Co-authors
Vegard Kolbjørnsrud
Oslo, Norway
[email protected]
Richard Amico
Boston, Massachusetts
[email protected]
Endnotes
I From April 2014 through October 2015, the Accenture Institute
for High Performance conducted 37 executive interviews that
incorporated insights from seven distinct industries and nine
countries on the topic of leading the digital enterprise. In doing
so, clients shared their experiences on their company’s digital
transformation efforts, industry developments, the evolution of
their roles in relation to digital disruption, and how to keep up
with increasingly tech-savvy employees and customers.
2 These initiatives included restructurings, acquisitions,
technology implementations, cost reductions, downsizings, and
new product entries. The organizations studied were across a
wide range, spanning 50 industries and 25 countries.
Copyright © 2015 Accenture. All rights reserved.
Accenture, its logo, and High Performance Delivered
are trademarks of Accenture.
About Accenture
Accenture is a global management consulting, technology services
and outsourcing company, with more than 358,000 people serving
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experience, comprehensive capabilities across all industries and
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them become high-performance businesses and governments. The
company generated net revenues of US$31.0 billion for the fiscal
year ended Aug. 31, 2015. Its home page is www.accenture.com.
About Accenture Strategy
Accenture Strategy operates at the intersection of business and
technology. We bring together our capabilities in business, technology, operations and function strategy to help our clients envision and
execute industry-specific strategies that support enterprise-wide
transformation. Our focus on issues related to digital disruption,
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helps drive both efficiencies and growth. For more information,
follow @AccentureStrat or visit www.accenture.com/strategy.
About the Accenture Institute
for High Performance
The Accenture Institute for High Performance develops and
publishes practical insights into critical management issues and
global economic trends. Its worldwide team of researchers connects
with Accenture’s consulting, technology and outsourcing leaders
to demonstrate how organizations become and remain high
performers through original, rigorous research and analysis.
For more information, please visit www.accenture.com/institute.
Methodology
In August/September 2015 the Accenture Institute for High
Performance surveyed 1,770 first-line, middle-level and executivelevel managers from 14 countries, representing 17 distinct
industries. The goal of this survey was to assess the potential
impact of cognitive computing on these managers’ jobs, and also
understand their perceptions of their current tasks and skills, as well
as the future of their positions. We defined intelligent machines as
computers and applications that collect and analyze data, make
informed decisions or recommendations for action, and learn
from experience.